There is a strong unmet need for a low-cost and convenient technology that can assist researchers and healthcare personnel in gathering vascular data. Such vascular imaging technology could assist in the short term, clinica research on the diagnostics, disease progression and effect of treatment/prevention strategies. In the long term, the same technology could integrate into the healthcare system for diagnosis, monitoring and management of disease in primary care environments, especially relevant for the aging population that may have restricted mobility. Diseases that are thought to show vascular symptoms or manifestations in the retina include diabetic/hypertensive retinopathies, stroke, cardiovascular disease and Alzheimer's disease. Skin vasculature could be monitored for identification of melanomas, classification of wounds/burns, assessment of healing, and titration of therapy (through evaluation of skin vasculature). Our team has developed an optical imaging platform based on laser speckle contrast imaging (LSCI) technology that can, for the first time, probe individual microvesses for their diameters, local density, and blood flow over a large field of view without the need for any contrast agents. Vasoptic Medical, Inc. is seeking to develop further and commercialize this technology, originally created at Johns Hopkins University, in an effrt to make vascular imaging low-cost and available to clinicians, healthcare workers, and researchers at large. Specifically in this Phase I, we will develop and make available to researchers: (a) a powerful LSCI-based software suite that can image blood vessel diameters, density and flow and enable comparison in longitudinal experiments. (b) a low-cost and portable implementation of the LSCI platform (ezLSCI) by designing a novel complementary metal oxide semiconductor (CMOS) imager chip that will match the sensitivity, noise, and resolution characteristics of current CCD cameras while offering considerable improvements in power consumption, size, speed, and system integration. An FPGA-based system operational module will control the device operation including illumination, image processing and image storage/transmission. The performance of the ezLSCI system and software will be characterized in preclinical models of retinal imaging and skin imagin. The ability of the ezLSCI system to discriminate healthy retinal blood flow from decreased retinal blood flow, common in disease conditions, will be demonstrated through the systemic administration of a vasoconstrictive agent. Further, the ability of the ezLSCI system to monitor the effects of therapeutic interventions will be demonstrated in a skin wound healing model with topical administration of an anti-angiogenic agent. Upon successful completion of Phase I milestones, our Phase II effort will comprise a more rigorous validation of the ezLSCI for skin imaging in a porcine model and a proof-of-concept clinical study with due regulatory approvals. We will seek private investment to support a clinical study that investigates the use of ezLSCI for early detection of retinopathy.